KGCODE-Tab Results for SemTab 2022
This paper presents the results of KGCODE-Tab in the tabular data to knowledge graph matching contest SemTab 2022. As an efficient tabular data linking system, KGCODE-Tab is intended to participate in three tasks of the content: Column Type Annotation (CTA), Cell Entity Annotation (CEA), and Columns Property Annotation (CPA). The specific techniques used by KGCODE-Tab will be introduced briefly. The strengths and weaknesses of KGCODE-Tab will also be discussed.
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Datasets
| Task | Dataset | Model | Metric Name | Metric Value | Global Rank | Benchmark |
|---|---|---|---|---|---|---|
| Column Type Annotation | BiodivTab | KGCODE-Tab | F1 (%) | 86.7 | # 1 | |
| Cell Entity Annotation | BiodivTab | KGCODE-Tab | F1 (%) | 91.1 | # 1 | |
| Column Type Annotation | GitTables-SemTab-DBP | KGCODE-Tab | F1 (%) | 58.7 | # 1 | |
| Column Type Annotation | GitTables-SemTab-SCH | KGCODE-Tab | F1 (%) | 69.3 | # 1 | |
| Column Type Annotation | ToughTables-DBP | KGCODE-Tab | F1 (%) | 48 | # 1 | |
| Cell Entity Annotation | ToughTables-DBP | KGCODE-Tab | F1 (%) | 82.7 | # 2 | |
| Column Type Annotation | ToughTables-WD | KGCODE-Tab | F1 (%) | 54.3 | # 4 |
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